Trajectory tracking control of a coaxial rotor drone: Time-delay estimation-based optimal model-free fuzzy logic approach

This paper proposes a control algorithm for controlling the position and attitude of a coaxial rotor drone without knowing the model dynamics. To overcome the major drawback of model-dependent approaches, an optimal model-free fuzzy controller (OMFFC) based on the estimation of the unknown dynamic function of the system is proposed. A time-delay estimation (TDE) technique is effectively exploited to approximate the unknown dynamic function of the system. The estimation error is then offset using a robust adaptive fuzzy logic compensator. Based on Lyapunov stability arguments, the global asymptotic stability of the coaxial rotor drone system is proven. Moreover, a flower pollination-based algorithm is also proposed to generate the optimal parameters to address the trade-off between optimal tracking performance and the design conditions related to the closed-loop stability requirements. The numerical simulations illustrate how the proposed methodology leads to the best performance, as well as less computational complexity compared to the standard proportional-integral-derivative and time-delay estimation-based controllers in the presence of external disturbances.

Robust fault diagnosis and fault-tolerant control for nonlinear quadrotor unmanned aerial vehicle system with unknown actuator faults

This article addresses the problem that quadrotor unmanned aerial vehicle (UAV) actuator faults, including small-amplitude bias faults and gain degradation, cannot be detected in time. A hybrid observer, which combines the fast convergence from adaptive observer and the strong robustness from sliding mode observer, is proposed to detect and estimate UAV actuator faults accurately with model uncertainties and disturbances. A nonlinear quadrotor UAV model with model uncertainties and disturbances is considered and a more precise unified expression for actuator faults that do not require knowing where the upper or lower bound is provided. The original system is decomposed into two subsystems by coordinate transformation to improve detection accuracy for small amplitude bias faults and avoid external influences. The hybrid observer is then designed to estimate subsystem states and faults with good stability by selecting a Lyapunov function. A fault-tolerant controller is obtained depending on fault estimation by compensating the normal controller (proportion integral differential [PID] controller). Several numerical simulations confirmed that unknown actuator faults can be accurately detected, estimated, and compensated for even under disturbance conditions.

High-precision prescribed-time path following for quadrotor

A high-precision prescribed-time guidance law is developed for a quadrotor to accomplish precise path following at predesigned time T. Firstly, a new control structure is proposed for a quadrotor to perform fixed-velocity back-to-turn flying mode by introducing four controllers, which can realize a non-sideslip and bank-to-turn flight scheme just like a fixed-wing unmanned aerial vehicle. Then, prescribed-time guidance law is presented based on fixed-velocity back-to-turn flying mode via combining sliding mode control with a compensation function [Formula: see text] to improve tracking precision of conventional methods. Compensation function [Formula: see text] is designed to make state error achieve convergence at prescribed time exactly. Meanwhile, global sliding mode is established to enhance robustness of the system. Then, the stability and characteristic of prescribed-time convergence are proved strictly. Finally, simulations with a 6-degree-of-freedom quadrotor model are carried out to demonstrate the effectiveness and superiority of prescribed-time guidance law by comparing with traditional guidance law.